For solving linear programs and mixed-integer linear programs with Prolog, I recommend the CLP(Q) and CLP(R) libraries of SICStus Prolog. See for example: http

For solving linear programs and mixed-integer linear programs with Prolog, I recommend the CLP(Q) and CLP(R) libraries of SICStus Prolog. See for example: https://sicstus.sics.se/sicstus/docs/3.7.1/html/sicstus_32.html https://sicstus.sics.se/sicstus/docs/3.7.1/html/sicstus_32.h... For discrete optimization tasks, also check out the integer constraint solver that ships with SICStus Prolog. See especially the combinatorial constraints: https://sicstus.sics.se/sicstus/docs/4.1.0/html/sicstus/Combinatorial-Constraints.html#Combinatorial-Constraints https://sicstus.sics.se/sicstus/docs/4.1.0/html/sicstus/Comb... As to the relation between Prolog and operations research: Prolog systems internally use methods from operations research to efficiently solve optimization tasks; in addition to that, you can of course also implement every OR algorithm in Prolog. For many commercial users of SICStus Prolog, the efficiency of its constraint solvers are an important reason for buying a licence.